The Operations Components provide common math operations that can be applied to layers in a neural network, and more generally, to tensors and matrices.
This is typically the last layer of the model in cases where you only want a single answer rather than a distribution (e.g., for classification).
- Dimension: specifies which axis contains the inputs on which to compute Argmax.
Combines two or more layers within a neural network such as when building skip connections.
- Number of inputs: specifies the number of input Components to merge. Adjusting this, sets the number of input sockets available in the Component to which other Components can be dragged and connected to.
- Operation: specifies the type of merge to perform. Can be set to:
- Concatenate: concatenates the values from each input. You can also set which dimension you want to concatenate on, where -1 defaults to the last dimension.
- Subtraction: subtracts the values from each input.
- Addition: adds the values from each input.
- Multiplication: multiples the values from each input.
- Division: divides the values from each input.
Switches between two different inputs and sends only the output from one of them at a time. This Component swaps every other time (i.e., first Component, second Component, first Component etc.).